Below are some takeaways from Sensemaking for Impact, a masterclass led by Jan Chipchase of Studio D Radiodurans that introduces his team’s approach to qual research strategy to generate inspired, prioritized insights, and high quality deliverables.

1. Evolution of understanding: hypothesis →data →information →knowledge →insight →wisdom

• Hypothesis: asking question based on existing frames/assumptions
• Data: collecting observations, quotes, ideas, photos/videos
• Information: giving data structure, synthesis where key points are highlighted
• Knowledge: finding patterns and relationships between parts of info
• Insight: reorganize the data in a way to reveal new perspectives, new way of seeing something
• Wisdom: insights put into a broader external perspective, learning from successful application of insights

Jan proposed “wisdom” as the next step after insight, which referenced knowing when to apply what degree of insights while allowing room for mistakes (which is an opportunity to learn from experience)

2. “We shape tools, then tools shape us” — digital tools prevent us from being fully immersed in the sketchy, exploratory, rough phase where early ideas and divergence happen. Digital notes creates the appearance of being “completed” which make us less willing to throw away bad ideas. A good workflow provides your team a manageable process. Goal is to have a sense of flow, neither anxiety nor boredom

3. Making sure the ratio of time for data collection (observations, connections, artifacts) →sensemaking (synthesis, identifying patterns, iterating on frameworks, reporting) gives much more time for sensemaking

4. People make sense of the world through stories. Reporting involves storytelling to an audience: when you tell a story, gathering a broader perspective on your audience’s values, culture and language allows you communicate their story in a way that is memorable/emotional

5. Having a naming strategy ensures that everyone refers to things in the same way; the role of a data manager ensures data quality (archive, consistency and categorization)

6. While technology, context, society may change, underlying human drivers stay the same (or changes much more slowly)

7. Memories live inside situations, emotions, expectations and locations. Researcher’s role is to learn how to talk about sensitive or taboo subjects in a way that is appropriate and respectful

8. Data recall decreases exponentially over time, with each person that hears and shares the story; sometimes meaning/interpretation is added to feedback which makes it even more inaccurate. Debrief sessions and reinforce key themes with your team when possible

9. When sharing insights, invest in your primary audience and think of your organization as a city. Within your city are existing biases, frameworks, rituals, values and language. How would you propose change in your city?

10. Terms

• Archetype: attitudes-based profile of a market segment, based on real people
• Framework: a distinct way of organizing and deciding the meaning of data
• Organizational metabolism: ability of an organization to ingest certain types of data, understand how to apply it
• Data wall: shared space for a team to collaborate on early ideas and frameworks, the current state of thinking.
• Rate of absorption: maximum amount of information a team can take in and categorize
• Thrulines: making sure insight is traceable to its original source